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Anna Eckerdal; Anders Berglund; Michael Thuné – European Journal of Engineering Education, 2024
Learning in the computer laboratory is an important component when students learn computer programming. In this article, we analyse empirical data on novice students working in pairs in the laboratory. Using an approach inspired by phenomenography and variation theory, we specifically focus on how students' learning of theory and their learning of…
Descriptors: Programming, Theory Practice Relationship, Higher Education, Computer Science Education
Ana E. Redstone; Tian Luo – TechTrends: Linking Research and Practice to Improve Learning, 2024
This article focuses on the practical implementation of Universal Design for Learning (UDL) in an online computer science course, articulating the collaborative efforts between the instructional designer (the first author) and the faculty member to redesign the course using UDL principles. Specific instances of redesigned learning modules and…
Descriptors: Electronic Learning, Computer Science, Student Empowerment, Higher Education
Competitive Programming Participation Rates: An Examination of Trends in U.S. ICPC Regional Contests
Jeremy J. Blum – Discover Education, 2023
A wide range of benefits have been posited from participation in competitive programming contests. However, an analysis of participation in north American regional contests in the International Collegiate Programming Contest (ICPC) shows that participation in these contests is sharply declining, coinciding with the COVID-19 pandemic. Moreover,…
Descriptors: Programming, Higher Education, Competition, Trend Analysis
Adrian Salguero – ProQuest LLC, 2024
Introductory computer programming (i.e. CS1) is the entry point into the computer science major at higher education institutions worldwide. It introduces foundational concepts to students that are then built upon in future courses. Computer science as a whole has struggled to attract and retain students in the major, particularly women and…
Descriptors: Computer Science, Programming, Introductory Courses, Disproportionate Representation
Ishaq, Muhammad; Abid, Adnan; Farooq, Muhammad Shoaib; Manzoor, Muhammad Faraz; Farooq, Uzma; Abid, Kamran; Helou, Mamoun Abu – Education and Information Technologies, 2023
Fundamentals of Database Systems is a core course in computing disciplines as almost all small, medium, large, or enterprise systems essentially require data storage component. Database System Education (DSE) provides the foundation as well as advanced concepts in the area of data modeling and its implementation. The first course in DSE holds a…
Descriptors: Databases, Computer Science Education, Required Courses, Information Storage
David R. Firth; Adam Gonzales; Michelle Louch; Bryan Hammer – Information Systems Education Journal, 2025
ChatGPT is having an impact on students, and information systems (IS) and computing academic professionals alike. Our goal for this paper is to help faculty and students know the conditions in which generative AI such as ChatGPT should or should not be used. To that end, we describe the development of a 2x2 matrix. On the horizontal axis we have…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Information Systems
Ahmad D. Suleiman; Daqing Hou; Yu Liu; Jan DeWaters; David C. Shepherd; Juliana G. De Souza – ACM Transactions on Computing Education, 2025
In recent years, there has been a rise in recognition of the need for computing education to bridge the gap between academia and industry. In addition, educational researchers are also interested in increasing student engagement by grounding learning experiences in real-life concerns, community issues, or personal interests. Unfortunately,…
Descriptors: Computer Science Education, Higher Education, Active Learning, Student Projects
Noelle Brown; Benjamin Xie; Ella Sarder; Casey Fiesler; Eliane S. Wiese – ACM Transactions on Computing Education, 2024
The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the "Association for Computing Machinery" computing education venues that describe teaching ethics in higher-education…
Descriptors: Ethics, Computer Science Education, Higher Education, Teaching Methods
Fulya Kula; Nelly Litvak; Tracy S. Craig – IEEE Transactions on Education, 2024
The sample mean in statistics is a concept of great importance, with its properties being extensively utilized in other areas, such as computer science. This research centers on the concept of the sample mean and its characteristics in a cohort of computer engineering students undertaking a required course in statistics at a university in the…
Descriptors: Computer Science Education, Engineering Education, Learning Processes, Statistics
A Comparison of Generative AI Solutions and Textbook Solutions in an Introductory Programming Course
Ernst Bekkering; Patrick Harrington – Information Systems Education Journal, 2025
Generative AI has recently gained the ability to generate computer code. This development is bound to affect how computer programming is taught in higher education. We used past programming assignments and solutions for textbook exercises in our introductory programming class to analyze how accurately one of the leading models, ChatGPT, generates…
Descriptors: Higher Education, Artificial Intelligence, Programming, Textbook Evaluation
A. R. Piña; Shams El-Adawy; Mike Verostek; Brett T. Boyle; Mateo Cacheiro; Matt Lawler; Namitha Pradeep; Ella Watts; Colin G. West; H. J. Lewandowski; Benjamin M. Zwickl – Physical Review Physics Education Research, 2025
Quantum information science and engineering (QISE) is rapidly gaining interest from those within many disciplines, and higher education needs to adapt to the changing landscape. Although QISE education still has a strong presence and roots in physics, the field is becoming increasingly interdisciplinary. There is a need to understand the presence…
Descriptors: Quantum Mechanics, Information Science, Engineering Education, Physics
Beaudoin, Laurent; Avanthey, Loïca – Education and Information Technologies, 2023
In this article, we present an educational reform we implemented a few years ago to respond to a marked drop in the success of students entering higher education in computer science. The main objective of our reform is to adapt the teaching methods of Generation X-Y to Generation Y-Z or more. To do this, we propose two approaches. First, to make…
Descriptors: Digital Literacy, Computer Science Education, Electronic Learning, Distance Education
Robert Chapa – ProQuest LLC, 2024
While the cybersecurity landscape continually evolves, with new technologies, attack vectors, and defense mechanisms emerging regularly, cybersecurity certificate programs remain challenged to stay current and relevant, often resulting in the delivery of outdated course content in existing programs. Scholars note that the absence of standardized…
Descriptors: Program Development, Computer Security, Electronic Learning, Certification
Holanda, Maristela; Da Silva, Dilma – IEEE Transactions on Education, 2022
Contributions: The underrepresentation of women in computer science (CS) majors has long been a focus of attention in many academic documents, the majority of them from the United States and Europe. There is, however, a lack of information about educational interventions (EIs) for women in computing in Latin America. The contribution of this…
Descriptors: Foreign Countries, Hispanic American Students, Disproportionate Representation, Computer Science
Victor-Alexandru Padurean; Tung Phung; Nachiket Kotalwar; Michael Liut; Juho Leinonen; Paul Denny; Adish Singla – International Educational Data Mining Society, 2025
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses…
Descriptors: Automation, Student Writing Models, Feedback (Response), Programming

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